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<body>
Contains all classes that realize a conditional box plot. A box plot displays some robust 
statistcal parameters for numerical attributes and identifies extreme outliers. 
A box plot displays the robust statistical parameters: minimum, lower quartile, 
median, upper quartile and maximum. These parameters called robust, since they 
are not sensitive to extreme outliers.
The conditional box plot partitions values of one numeric column according to a nominal
column and creates box plots for this parts.
<p>
A box plot for one numerical attribute is constructed in the following way:
The box itself goes from the lower quartile (Q1) to the upper quartile (Q3). 
The median is drawn as a horizontal bar inside the box. The distance between Q1 
and Q3 is called the interquartile range (IQR).
<p>
Above and below the box are the so-called whiskers. They are drawn at the 
minimum and the maximum value as horizontal bars and are connected with the box 
with a dotted line. The whiskers never exceed 1.5 * IQR. This means if there 
are some data points which exceed either Q1 - (1.5 * IQR) or Q3 + (1.5 * IQR) 
than the whiskers are drawn at exactly these ranges and the data points are 
drawn seperatly as outliers.
<p>
For the outliers the distinction between mild and extreme outliers is made.
As mild outliers are those datapoints p considered for which holds: <br />
p &lt; Q1 - (1.5 * IQR) and p &gt; Q1 - (3 * IQR) or <br />
p &gt; Q3 + (1.5 * IQR) and  p &lt; Q3 + (3 * IQR). <br />
In other words mild outliers are those data points which lay between 1.5 * IRQ 
and 3 * IRQ. Extreme outliers are those datapoints p for which holds: <br />
p &lt; Q1 - (3 * IQR) or p &gt; Q3 + (3 * IQR). <br />
Thus, three times the box width (IQR) marks the boundary between 
"mild" and "extreme" outliers. Mild outliers are painted as dots while extreme 
outliers are displayed as crosses. In order to identify the outliers they can 
be selected and hilited. This provides a quick overview over extreme 
charateristics of a dataset.
</body>
